Internship- Computer Vision and Deep Learning (m/f/d)
Our CARIDIANS are developing vehicle functions such as driver assistance systems, a next-generation infotainment platform, power electronics and charging technology, and digital services in and around the vehicle.
Our software can already be found in Volkswagen ID. models and will soon power Audi and Porsche vehicles with the E3 1.2 platform in 2024.
It's no easy task, but with experts like you, we can shape the future of mobility. Join us at CARIAD and be part of this exciting journey!
YOUR TEAM
We are looking for an intern to be part of cutting-edge research in camera-based perception in ADAS & AD. You will be carrying out research in the area of computer vision.
Our team is known as the competence center for processes, methods and tools to enable the CARIAD Tech Centers in their daily work. The competence center focusses on the areas of Engineering Data Backbone, Business Intelligence & Reporting and Artificial Intelligence.
You get the chance to dive into the field of research and find ways to improve the trustworthiness and robustness of deep learning systems under different conditions and scenarios. Join us and help us tackle the limitations of current systems using the knowledge of foundation models.
WHAT YOU WILL DO- Collaborate with our PhD students in the development of an Out-of-Distribution (OoD) detection method
- Support the implementation of baseline methods in this field
- Implement an automatic test pipeline and perform evaluations in different scenarios
- Enrolled Master's student in Computer Science, Electrical Engineering or equivalent field
- Independent, motivated, and structured thinking
- Knowledge in machine learning and computer vision
- Hands-on experience in software development, proficiency in Python and Deep Learning frameworks, preferably PyTorch
- Experience with OoD detection, uncertainty estimation, or foundation models is advantageous
- Hands-on experience with cloud computing services, preferably Azure would be beneficial
- Fluent in English
- Remote work options
- Duration: 3 to 6 months
- 35 hour working week
- If you have further questions about the candidate journey at CARIAD, please contact us: careers@cariad.technology
YOUR RECRUITING CONTACT
Carmen Dörwald